Divergent values and perspectives drive three distinct viewpoints on grizzly bear reintroduction in Washington, the <scp>United States</scp>
Notice bibliographique
Résumé
Abstract The success or failure of apex carnivore reintroduction efforts can hinge on understanding and attending to diverse viewpoints of those involved in and impacted by reintroductions. Yet, viewpoints vary widely due to a suite of complex and intersecting factors, such as values, beliefs and sociocultural context. We ask, ‘what are the diverse viewpoints that exist surrounding apex carnivore recovery and what kinds of emotional, analytical and values‐based judgments might people use to construct their viewpoints?’ We used Q‐methodology to identify distinct, generalized viewpoints and areas of overlap and divergence between them, surrounding a proposal to reintroduce grizzly bears ( Ursus arctos horribilis ) to the North Cascades Ecosystem, USA. Q‐methodology combines qualitative and quantitative methods by asking purposefully sampled respondents to sort various statements on a given topic into an ordered grid. We found three distinct viewpoints among 67 respondents using factor analysis and responses to open‐ended questions about the sorting exercise. Two of these viewpoints represent essentially polarized perspectives corresponding to deeply normative notions about grizzly bear recovery, where one views reintroducing bears as a moral requisite, and the other views it as inappropriate and risky. These viewpoints primarily diverged on their perceptions of risk and perspectives about our collective responsibilities to and appropriate relationships with others (i.e. ‘relational values’). The third viewpoint was distinguished by its prioritization of practical considerations and views reintroducing bears as impractical and not sensible . Our analysis underscores the need to identify and attend to latent viewpoints that may be overlooked in the polarized public discourse as well as the multiple value systems and perceptions of risk that are integrated in perspectives on grizzly bear reintroduction. Additionally, our broadly defined identity groups were of very little utility in predicting viewpoints in this study, highlighting the importance of avoiding assumptions about people's views based on their identities and interests. We argue that forefronting conversations about responsibilities and appropriate relationships is critical for finding acceptable paths forward in such recovery efforts. We discuss the management implications of these findings for the North Cascades grizzly bear reintroduction, and for other large carnivore reintroductions. Read the free Plain Language Summary for this article on the Journal blog.
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Comment cette classification a été obtenuedéplier
Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,000 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».